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New Research Suggests That Neurostimulation, Or Zapping The Brain With Electrical Currents, Can Heighten Math Skills By Exciting Learning Abilities

Rido - stock.adobe.com- illustrative purposes only, not the actual person

Many students find themselves tripping up over the complex formulas that come with advanced math.

However, new research points to neurostimulation as a potential game-changer for those who have always had a tricky time with numbers and fractions.

A collaborative effort between researchers at the Universities of Surrey and Oxford, Radboud University, and Loughborough University brought this exciting study to life.

The team delved deep into how neurostimulation affects learning. But, even though there’s a growing curiosity about neurostimulation as a neurological technique that is non-invasive, we are still in the early days of understanding its potential side effects and influence on learning.

Neurostimulation broadly encompasses various methods that target the direct stimulation of the nervous system, predominantly through electrical currents, aiming to alter or regulate its activities.

For this specific study, the researchers opted for electrical noise stimulation, a distinct type of neurostimulation defined by its randomized electrical pulses.

“Learning is key to everything we do in life– from developing new skills, such as driving a car, to learning how to code. Our brains are constantly absorbing and acquiring new knowledge,” said Professor Roi Cohen Kadosh, the study’s leader.

“Previously, we have shown that a person’s ability to learn is associated with neuronal excitation in their brains. What we wanted to discover in this case is if our novel stimulation protocol could boost, in other words, excite, this activity and improve mathematical skills.”

For this study, the team recruited 102 participants and tested their math skills through a series of multiplication tasks. Afterward, the participants were divided into four groups.

Rido – stock.adobe.com- illustrative purposes only, not the actual person

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